Theses and Dissertations at Montana State University (MSU)

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    The neurology of learning in a secondary science classroom
    (Montana State University - Bozeman, College of Letters & Science, 2021) Campbell, Carlan Lynn; Chairperson, Graduate Committee: Greg Francis
    By actively teaching students about the neurology behind their learning students will integrate positive learning practices into their education and everyday lives. The questions associated with the focus statement were: Can teaching about the neurology behind learning increase tenacity in the classroom? Does implementing a lesson about how the human brain learns impact students' scores, demeanor, and work ethic? Teaching students about neurology resulted in students who are more likely to implement positive learning practices including, tenacity, increased test scores through study skills, and fewer behavioral redirects. Pre- and post- content tests, a Likert style survey, an unsolvable problem set, an interview, and a categorized behavioral journal were used as data collection instruments. Data were processed and analyze using both qualitative and quantitative methods. The results suggested teaching students about neurology has a positive impact in the classroom. After learning about neurology, students were more likely to spend a longer period of time working on a puzzle that does not have a solution than the same students before learning about neurology. Students who learned about neurology improved more on their pre- post- test when compared to the same students before learning about neurology. When students were asked, if they felt that learning about neurology was valuable, the majority of them said 'yes'. One student said, 'I will stick with problems now more than ever. If I don't understand something, I know that if I keep trying eventually, I will build that connection.' Ultimately it is evident that students who were taught about neurology in the classroom are more likely to implement and consistently use positive learning practices, display appropriate behaviors, and increased the likelihood that a student would stick with a problem for a longer period of time if they were directly taught about the processes of their brain while learning.
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    Techniques for improving activity based biosensors: a Kuhl platform for engineering
    (Montana State University - Bozeman, College of Agriculture, 2020) Thomas, Merrilee Anne; Chairperson, Graduate Committee: Thomas Hughes and Susy C. Kohout (co-chair); Thomas E. Hughes was a co-author of the article, 'Optically activated, customizable, excitable cells Kuhl platform for evolving next gen biosensors' submitted to the journal 'PLOS One' which is contained within this dissertation.
    According to Kuhn, ''there are three classes of problems - determination of significant facts, matching of facts with theory, and articulation of that theory (Kuhn 2012).'' The current paradigm in molecular neuroscience is that there is a need for revolutionary tool development in neuroscience. Interestingly, the need for better tools in neuroscience is to answer neuroscience theories and provide the determination and articulation of those theories. Currently, the neuroscientist's toolbox is growing and the ways in which those tools are used is rapidly changing. Neuroscience underwent a revolution when we were able to take single-cell recording in vivo and then assign field properties to individual neurons based upon those responses (O'Keefe and Bouma 1969; O'Keefe and Dostrovsky 1971; Moser et al. 1995). Scientists became adept at imaging increasingly smaller regions of the functioning human brain (Price 2012). We have since been able to genetically encode and manipulate proteins and pathways while recording from them using fluorescence (Southern and Berg 1982; Chalfie 2009). In vitro and in vivo we have harnessed the use of light to stimulate or inhibit specific neurons or ligands (Boyden 2011; Adamantidis et al. 2007). These tools are just the beginning and by no means is this an exhaustive list. We introduce the Kuhl synthetic cell system that provides a customizable de-novo excitable cell. The Kuhl system is activated using a blue light photo activated cyclase bPAC. It can be used to create better tools to image the brain and can be used to screen multi-color fluorescent sensors. Interestingly, sensors that are within bPACs activation spectrum can be used in these synthetic cells. We show that both red and green Ca 2+ sensors can be imaged simultaneously, and both Ca 2+ and Voltage sensors can be screened in the Kuhl system. The Kuhl system has the potential to be used to screen for drug compounds and in theory, they could be used in studying pathways that are less understood, such as the mTOR pathway.
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    Design and implementation of a real-time system to characterize functional connectivity between cortical areas
    (Montana State University - Bozeman, College of Engineering, 2017) Parsa Gharamaleki, Mohammadbagher; Chairperson, Graduate Committee: Brendan Mumey
    Despite a thorough mapping of the anatomical connectivity between brain regions and decades of neurophysiological studies of neuronal activity within the various areas, our understanding of the nature of the neural signals sent from one area to another remains rudimentary. Orthodromic and antidromic activation of neurons via electrical stimulation ('collision testing') has been used in the peripheral nervous system and in subcortical structures to identify signals propagating along specific neural pathways. However, low yield makes this method prohibitively slow for characterizing cortico-cortical connections. We employed recent advances in electrophysiological methods to improve the efficiency of the collision technique between cortical areas. There are three key challenges: 1) maintaining neuronal isolations following stimulation, 2) increasing the number of neurons being screened, and 3) ensuring low-latency triggering of stimulation after spontaneous action potentials. We have developed a software-hardware solution for online isolations and stimulation triggering, which operates in conjunction with two hardware options, Hardware Processing Platform (HPP) or a Software Processing Platform (SPP). The HPP is a 'system on a chip' solution enabling real-time processing in a re-programmable hardware platform, whereas the SPP is a small Intel Atom processor that allows soft real-time computing on a CPU. Employing these solutions for template matching both accelerates spike sorting and provides the low-latency triggering of stimulation required to produce collision trials. Recording with a linear tetrode array electrode allows simultaneous screening of multiple neurons, while the software package coordinates efficient collision testing of multiple user-selected units across channels. This real-time connectivity screening system enables researchers working with a variety of animal models and brain regions to identify the functional properties of specific projections between cortical areas in behaving animals.
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    A study of the phenomenological and neurological approach to intelligence and their relationship to intelligence testing
    (Montana State University - Bozeman, 1975) Winburn, Everett Lee; Chairperson, Graduate Committee: Richard K. Horswill
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    A non-autonomous bursting model for neurons
    (Montana State University - Bozeman, College of Letters & Science, 2007) Latulippe, Joe Jean-Marc; Chairperson, Graduate Committee: Mark Pernarowski
    Certain mammalian visual neurons exhibit On and Off responses when given a light stimulus. In addition to these responses, [51] showed that for retinal ganglion cells, the neuron will also exhibit a Mixed response when given two simultaneous stimuli in different regions of the cell's receptive field. This Mixed response is a nonlinear combination of the On and Off responses. In this dissertation, a single cell model which can reproduce On, Off, and Mixed responses is developed and examined using leading order analyses and averaging. This model is developed from a current balance equation which includes a non-autonomous input I(t), and consists of three coupled, first-order nonlinear differential equations which describe the dynamics of the membrane potential of the cell. When I(t) is assumed to be a constant current pulse, the On and Off responses can be reproduced but will depend on both the duration and the amplitude of the input. When I(t) is assumed to be monotone slowly decreasing, the model can reproduce the nonlinear properties for two simultaneous stimuli. In this dissertation, conditions which will guarantee each type of response will be found using the different subsystems of the model.
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    Characterization of the neural codebook in an invertebrate sensory system
    (Montana State University - Bozeman, College of Letters & Science, 2007) Aldworth, Zane Nathan; Chairperson, Graduate Committee: John P. Miller; Tomas Gedeon (co-chair)
    An outstanding problem in neuroscience is to describe the relationship between various stimulus sources in the environment and how they are represented by patterns of activity in nervous systems, a problem generically referred to as 'neural coding'. Most previous methods developed to address this problem have assumed a linear relationship between environmental stimuli and neural responses, and generally relied on measures of the mean state of the environment preceding neural activity to characterize the stimulus-response transformation. The goal of this thesis is to develop new methods of characterization that extend earlier work, and to demonstrate the utility of these new methods through application to an invertebrate sensory system. All applications of the methods developed in this thesis were carried out in the cercal system of crickets. The cercal system mediates the detection and analysis of low velocity air currents, and is implemented around an internal representation of air current direction that demonstrates the essential features of a continuous neural map. The stimulus feature selectivity, timing precision and coding characteristics of two bilateral pairs of primary sensory interneurons of the cercal system were characterized using three novel techniques. First, estimates of the cells' feature selectivity that take the natural variance in stimulus-response latency (i.e., spike 'jitter') into account were derived. Second, the cells' stimulusresponse relationship was probed for specific non-linear aspects that could constitute 'temporal' encoding. Third, an iterative stimulation paradigm was used to test and refine the predictions of the cercal system's stimulus selectivity. Compared to earlier characterization of this system, these new analytical procedures yield significantly different estimates of the stimulus feature selectivity of these cells. A 'code book' for the stimulus-response characteristics of these cells is presented, with emphasis on demonstrating instances where a cell represents different stimuli with distinct spike 'code-word' patterns.
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